A SISO FMCW radar based on inherently frequency scanning antennas for 2-D indoor tracking of multiple subjects

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10 Citations (Scopus)

Abstract

The contextual non-invasive monitoring and tracking of multiple human targets for health and surveillance purposes is an increasingly investigated application. Radars are good candidates, since they are able to remotely monitor people without raising privacy concerns. However, radar systems are typically based on complex architectures involving multiple channels and antennas, such as multiple-input and multiple-output (MIMO) or electronic beam scanning, resulting also in a high power consumption. In contrast with existing technologies, this paper proposes a single-input and single-output (SISO) frequency-modulated continuous wave (FMCW) radar in combination with frequency scanning antennas for tracking multiple subjects in indoor environments. A data processing method is also presented for angular separation and clutter removal. The system was successfully tested in five realistic indoor scenarios involving paired subjects, which were either static or moving along predefined paths varying their range and angular position. In all scenarios, the radar was able to track the targets, reporting a maximum mean absolute error (MAE) of 20 cm and 5.64 in range and angle, respectively. Practical applications arise for ambient assisted living, telemedicine, smart building applications and surveillance.

Original languageEnglish
Article number16701
Number of pages12
JournalScientific Reports
Volume13
Issue number1
Early online date4 Oct 2023
DOIs
Publication statusPublished - 4 Oct 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023, Springer Nature Limited.

Funding

This project has received funding from the European Union\u2019s Horizon Europe research and innovation program under the grant agreement N 101063966 (Marie Sk\u0142odowska-Curie IN-SIGHT project), by the \u201CAttrazione e Mobilit\u00E1 Internazionale dei Ricerca-tori\u201D program-CUP: H24I19000410005, and by the European Union under NEXTPERCEPTION project Grant No. ECSEL-2019-2-RIA, Reference: 876487.

FundersFunder number
European Union's Horizon 2020 - Research and Innovation Framework Programme876925
European Union's Horizon 2020 - Research and Innovation Framework ProgrammeN 101063966

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